Clinical trials to test new drugs, medical devices, and/or treatment regimens are traditionally conducted using a large population of test subjects, and may generate a large amount of data to be analyzed. Traditionally, software is manually written to analyze the data and produce reports. For each new trial, new software programs may need to be written to analyze the newly collected data. Only limited efficiencies can be gained from using standard artifacts that are reused from study to study, given that the studies may be sufficiently different in the data being analyzed and the artifact(s) being output. Accordingly, analyzing the data generated through a series of clinical trials has traditionally been an inefficient process that consumes a large amount of computing resources and computer programmer time to code and execute software.